Control Simulation of Single Inverted Pendulum Using Fuzzy Control

This project implements a control simulation for a single inverted pendulum using fuzzy control methodology. The simulation employs a Sugeno-type fuzzy controller to achieve stable pendulum balancing. In this experiment, we primarily fuzzify the pendulum's angle and angular velocity measurements, which serve as input variables to the fuzzy controller. The controller then performs inference operations based on the fuzzy rule base, generating fuzzy output signals through Mamdani-type reasoning. Subsequently, we apply defuzzification techniques (typically using weighted average methods for Sugeno models) to convert the fuzzy outputs into precise control signals that drive the pendulum's motion. Through this control simulation, we validate the effectiveness of fuzzy control in single inverted pendulum systems and gain deeper insights into fuzzy control principles and practical applications. Key implementation aspects include designing membership functions for input variables, establishing fuzzy rules based on control experience, and implementing real-time control signal calculation algorithms.